GPT OSS 120BvsQwen3.5 Plus 2026-04-20
GPT OSS 120B is cheaper than Qwen3.5 Plus 2026-04-20 at $0.18/M vs $0.4/M input tokens.
| Spec | GPT OSS 120B | Qwen3.5 Plus 2026-04-20 |
|---|---|---|
| Input price | $0.18/M tokens | $0.4/M tokens |
| Output price | $0.8/M tokens | $2.4/M tokens |
| Context window | 131K tokens | 1.0M tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Apr 2026 |
Our Verdict
GPT OSS 120B
Qwen3.5 Plus 2026-04-20
Not enough votes to call it. On the specs, nothing separates them.
Too close to call
Reviewing agent-written code?See a Brief PR report
API pricing
Cost per 1M tokens
GPT OSS 120B
Input
$0.18
2.2× cheaper
Output
$0.80
3.0× cheaper
Qwen3.5 Plus 2026-04-20
Input
$0.40
Output
$2.40
GPT OSS 120B is cheaper on both: 2.2× input, 3.0× output.
Where to run it
20 hosts, cheapest first
GPT OSS 120B19 hosts
AkashMLbf16$0.03 in$0.17 out131k99.9% upCoreWeavefp4$0.03 in$0.17 out131k99.9% upDekaLLMbf16$0.03 in$0.18 out131k99.2% upDeepInfrabf16$0.04 in$0.17 out131k98.8% upDigitalOcean$0.06 in$0.39 out128k99.8% upMancerfp8$0.06 in$0.50 out131k99.3% up
13 more hostsFewer hosts
Google Vertex AI$0.09 in$0.36 out131k99.9% upBasetenfp4$0.10 in$0.50 out128k100% upParasailfp4$0.10 in$0.75 out131k97.5% upSambaNova$0.14 in$0.95 out131k97.7% upAmazon Bedrock$0.15 in$0.60 out131k100% upGroq$0.15 in$0.60 out131k100% upNebiusfp4$0.15 in$0.60 out131k98.7% upSiliconFlowfp8$0.15 in$0.60 out131k95.8% upCerebrasfp16$0.35 in$0.75 out131k100% upNovitafp4degraded$0.05 in$0.25 out131k96.2% upPhaladegraded$0.15 in$0.60 out131k96.6% upTogetherdegraded$0.15 in$0.60 out131k94.9% upMaradegraded$0.15 in$0.75 out131k58.1% up
Qwen3.5 Plus 2026-04-201 host
Per million tokens. Prices and uptime via OpenRouter, checked 11 Sep 2026.
Writing DNA
Style Comparison
Similarity
54%
Qwen3.5 Plus 2026-04-20 uses 10.0x more emoji
GPT OSS 120B
Qwen3.5 Plus 2026-04-20
52%Vocabulary59%
19wSentence Length15w
0.28Hedging0.28
7.4Bold4.4
1.8Lists2.5
0.15Emoji1.53
0.73Headings0.76
0.17Transitions0.04
Based on 21 + 27 text responses
Research
What we learned reading every model
FAQ
Common questions
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